公开(公告)号：US20210166035A1

公开(公告)日：2021-06-03

申请号：US17120525

申请日：2020-12-14

Applicant: Google LLC

Inventor： Sanketh Shetty ,  Tomas Izo ,  Min-Hsuan Tsai ,  Sudheendra Vijayanarasimhan ,  Apostol Natsev ,  Sami Abu-El-Haija ,  George Dan Toderici ,  Susana Ricco ,  Balakrishnan Varadarajan ,  Nicola Muscettola ,  WeiHsin Gu ,  Weilong Yang ,  Nitin Khandelwal ,  Phuong Le

IPC: G06K9/00 ,  G06F16/783

Abstract: A computer-implemented method for selecting representative frames for videos is provided. The method includes receiving a video and identifying a set of features for each of the frames of the video. The features including frame-based features and semantic features. The semantic features identifying likelihoods of semantic concepts being present as content in the frames of the video. A set of video segments for the video is subsequently generated. Each video segment includes a chronological subset of frames from the video and each frame is associated with at least one of the semantic features. The method generates a score for each frame of the subset of frames for each video segment based at least on the semantic features, and selecting a representative frame for each video segment based on the scores of the frames in the video segment. The representative frame represents and summarizes the video segment.

公开(公告)号：US10482328B2

公开(公告)日：2019-11-19

申请号：US15722756

申请日：2017-10-02

Applicant: Google LLC

Inventor： Balakrishnan Varadarajan ,  George Dan Toderici ,  Apostol Natsev ,  Nitin Khandelwal ,  Sudheendra Vijayanarasimhan ,  Weilong Yang ,  Sanketh Shetty

IPC: G06K9/62 ,  G06K9/00 ,  G06F16/783 ,  G06F16/78 ,  G06K9/52 ,  H04N5/265

Abstract: A system and methodology provide for annotating videos with entities and associated probabilities of existence of the entities within video frames. A computer-implemented method identifies an entity from a plurality of entities identifying characteristics of video items. The computer-implemented method selects a set of features correlated with the entity based on a value of a feature of a plurality of features, determines a classifier for the entity using the set of features, and determines an aggregation calibration function for the entity based on the set of features. The computer-implemented method selects a video frame from a video item, where the video frame having associated features, and determines a probability of existence of the entity based on the associated features using the classifier and the aggregation calibration function.

公开(公告)号：US20180089200A1

公开(公告)日：2018-03-29

申请号：US15819050

申请日：2017-11-21

Applicant: GOOGLE LLC

Inventor： Balakrishnan Varadarajan ,  George Dan Toderici ,  Apostol Natsev ,  Weilong Yang ,  John Burge ,  Sanketh Shetty ,  Omid Madani

IPC: G06F17/30 ,  G06F17/24 ,  G06F17/27

CPC classification number: G06F16/24578 ,  G06F16/285 ,  G06F16/78 ,  G06F17/241 ,  G06F17/278

Abstract: Facilitating of content entity annotation while maintaining joint quality, coverage and/or completeness performance conditions is provided. In one example, a non-transitory computer-readable medium comprises computer-readable instructions that, in response to execution, cause a computing system to perform operations. The operations include aggregating information indicative of initial entities for content and initial scores associated with the initial entities received from one or more content annotation sources and mapping the initial scores to respective values to generate calibrated scores. The operations include applying weights to the calibrated scores to generate weighted scores and combining the weighted scores using a linear aggregation model to generate a final score. The operations include determining whether to annotate the content with at least one of the initial entities based on a comparison of the final score and a defined threshold value.